| Monte Carlo guided diffusion for Bayesian linear inverse problems GV Cardoso, YJ El Idrissi, S Le Corff, E Moulines ICLR International Conference on Learning Representations, 2024 | 28* | 2024 |
| State and parameter learning with PaRIS particle Gibbs G Cardoso, YJE Idrissi, SL Corff, É Moulines, J Olsson International Conference on Machine Learning. PMLR, 2023., 2023 | 9 | 2023 |
| Generative methods for sampling transition paths in molecular dynamics T Lelièvre, G Robin, I Sekkat, G Stoltz, GV Cardoso ESAIM: Proceedings and Surveys 73, 238-256, 2023 | 7 | 2023 |
| Br-snis: bias reduced self-normalized importance sampling G Cardoso, S Samsonov, A Thin, E Moulines, J Olsson Advances in Neural Information Processing Systems 35, 716-729, 2022 | 6 | 2022 |
| Diffusion posterior sampling for simulation-based inference in tall data settings J Linhart, GV Cardoso, A Gramfort, SL Corff, PLC Rodrigues arXiv preprint arXiv:2404.07593, 2024 | 3 | 2024 |
| Bayesian ecg reconstruction using denoising diffusion generative models GV Cardoso, L Bedin, J Duchateau, R Dubois, E Moulines arXiv preprint arXiv:2401.05388, 2023 | 2 | 2023 |
| ECG Inpainting with denoising diffusion prior L Bedin, G Cardoso, R Dubois, E Moulines Deep Generative Models for Health Workshop NeurIPS 2023, 0 | 1 | |
| Generative models for ECG data: theory and application. GV Cardoso Institut Polytechnique de Paris, 2024 | | 2024 |
| Particle-based, rapid incremental smoother meets particle Gibbs G Cardoso, E Moulines, J Olsson Statistica Sinica, 2022 | | 2022 |
| A Patient-Specific Single Equivalent Dipole Model G Cardoso, G Robin, A Arrieula, M Potse, M Haïssaguerre, E Moulines, ... 2022 Computing in Cardiology (CinC) 498, 1-4, 2022 | | 2022 |
| Leveraging an ECG Beat Diffusion Model for Morphological Reconstruction from Indirect Signals L Bedin, G Cardoso, J Duchateau, R Dubois, E Moulines The Thirty-eighth Annual Conference on Neural Information Processing Systems, 0 | | |
